Kioxia Corporation

Asuka Maki

Daisuke Miyashita

Kengo Nakata

Jun Deguchi

According to one embodiment, an arithmetic apparatus includes a non-volatile first memory, a second memory, and a controller. The first memory stores a model to be trained. The second memory has a smaller storage capacity than the first memory. The controller executes learning processing that updates a first parameter of the model based on a loss value obtained by inputting training data into the model stored in the first memory, and stores cumulative update information indicating a difference of the first parameter before and after the update in the second memory. In addition, the controller executes the learning processing using a second parameter in which the cumulative update information stored in the second memory is reflected in the first parameter read from the model stored in the first memory, and stores a difference between a third parameter obtained by updating the second parameter and the first parameter, in the second memory as the cumulative update information.

Arithmetic apparatus and arithmetic method

According to one embodiment, an information processing method includes: calculating a first feature amount of query data in a first field; calculating first similarity degrees between the first feature amount and second feature amounts in the first field; obtaining, based on the first similarity degrees, third feature amounts in a second field that are associated with feature amounts selected from the second feature amounts, the second field being different from the first field; calculating fourth feature amounts in the second field, for choices concerning the query data; calculating second similarity degrees between the third feature amounts and the fourth feature amounts; and selecting, based on the second similarity degrees, an answer to the query data among answer candidates corresponding to the third feature amounts.

Information processing method, information processing device, and computer system

An arithmetic operation device is provided that removes a part of parameters of a predetermined number of parameters from a first machine learning model which includes the predetermined number of parameters and is trained so as to output second data corresponding to input first data, determines the number of bits of a weight parameter according to required performance related to an inference to generate a second machine learning model, and acquires data output from the second machine learning model so as to correspond to the input first data with a smaller computational complexity than the first machine learning model.

Arithmetic operation device using a machine learning model, arithmetic operation method using a machine learning model, and training method of the machine learning model

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Kawasaki, Japan

Asuka Maki